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Data Quality Tools In Data Migrations
- 1. Using Data Quality tools in Data Migration Steve Tuck, 1 st October 2009
- 2. A brief history of Steve Tuck 18 years experience of data migrations & data quality Worked with leading technologies & companies
- 3. About Datanomic Data Management Software Specialist Founded 2001 Acquired Tranato 2005 Blue Chip Customer Base Global Deployments Global Partner Network
- 4. Using DQ tools in Data Migrations Moving data Where do things go wrong? How can data quality tools help? How do they fit with ETL? Q & A
- 5. Moving data Delivering the right data To the right place At the right time
- 6. Moving data Delivering the right data To the right place At the right time “ Most data migration projects fail to come in on-time and in-budget” Dylan Jones, Founder of DataMigrationPro.com and DataQualityPro.com, May 2009 “ 84% of data migration projects fail to meet expectations 64% deliver late 37% come in over budget” Philip Howard, Bloor Research (from Data Migration in the Global 2000, Sept. 2007)
- 7. Where do things go wrong? Little attention to data contents Some data is already broken Some gets lost or damaged in transit The target system needs data that is fit-for-purpose… This is a BUSINESS issue, not a question for IT alone
- 8. How can data quality tools help?
- 9. Understand the data Using data profiling to discover potential issues
- 10. Understand the data And collaborate with subject matter experts from the business
- 11. Understand the data Validate business critical information with targeted rules Screen out dummy & default values Identify missing and misfielded data Spot minimum state issues Refine migration data mappings
- 12. Improve the data Build rules from the data, not the documentation From simple LUTs to semantic parsing
- 13. Improve the data Clean and match logical entities to remove duplicates
- 14. Control the data Provide ongoing insight as data is prepared for migration and throughout the migration event Set quality thresholds as well as ones based on the volume of data moved
- 15. Data quality in data migrations
- 16. Summary Data quality tools ensure that the target system is loaded with fit-for-purpose data This requires collaboration between IT and business experts Rules are commonly developed iteratively DQ tools can also be used to monitor and maintain data standards in the target
- 17. Questions?
- 18. Steve Tuck Chief Strategy Officer +44 1223 228 435 [email_address] www.datanomic.com
Editor's Notes
- #7: Poor data quality cited as one of the top 3 reasons for failure. Google reports > 9,000 web pages referring to failed data migrations due to poor data quality … … that’s just pages added in the last month!